Random error in estimates is the problem we try to solve using formal methods of inference. Confidence intervals, e.g. those obtained from bootstrap resampling, are a solution.

In these 2 videos, we focus on the errors we make when we use data from a sample to tell us something about a whole population. We ask: “How wrong could I be?” We also show the difference between the effects of systematic biases and random errors as we take more and more observations.